By Li Yinong, SFC, 21st Century Business Herald

The rise of AI for Science is profoundly reshaping the paradigm of scientific research. As artificial intelligence becomes capable of predicting protein structures, screening drug targets, and running tens of thousands of experimental simulations in parallel, a fundamental question inevitably emerges: what is the enduring value of human scientific inquiry?

On February 3, the World Laureates Summit (WLS) concluded successfully in Dubai, United Arab Emirates. Over the course of three days, scientists, policymakers, and young leaders from around the world engaged in open dialogue and reached a deep consensus: in a world defined by uncertainty, basic science remains one of the few sources of certainty humanity can rely on. Breakthroughs in fundamental science often arise from the unknown—beyond existing cognition—a realm that algorithms have yet to truly reach.

At the same time, emerging technologies such as artificial intelligence and blockchain are creating historic opportunities to build new models of scientific collaboration and value sharing. In the past, scientists shaped how we understand the world; in the future, they will continue to work alongside new technologies and platforms to advance human progress in deeper and more enduring ways.

Why the Question of Science Never Ends

The mission of science is to understand the world—and our current understanding remains remarkably limited. Roger D. Kornberg, President of the World Laureates Association (WLA) and winner of the 2006 Nobel Prize in Chemistry, offered a striking example: “Our understanding of human biology is probably less than one percent.” It is precisely this vast unknown that makes the future of science boundless.

Throughout history, there have always been voices claiming that science was nearing its end. In the late 19th century, some believed that the framework of human knowledge was essentially complete, requiring only incremental improvements in engineering and application. There were even claims that “the edifice of physics had been built.” Yet in 1905, Albert Einstein’s three groundbreaking papers fundamentally transformed physics, shaping the discipline throughout the 20th century and beyond.

“Almost every generation claims, ‘Now we finally understand everything’—and that has always been nonsense,”said Joachim Frank, winner of the 2017 Nobel Prize in Chemistry, in an interview with Southern Finance Omnimedia. “Whenever you hear such statements, you should simply ignore them.”

Science, far from approaching an endpoint, may in fact be on the verge of another explosion. “Some people argue that all the low-hanging fruit has already been picked,” Kornberg noted. “But the opposite is true—the most important discoveries are still ahead of us.” In his view, basic research is the only sustainable engine of social and economic progress, and the fuel that drives this engine will always be the next question.

What Is the Role of Human Scientists in the Age of AI?

In an era when AI can predict molecular structures, identify drug targets, and perform massive parallel simulations, what remains the role of human scientists?

Frank emphasized that AI’s predictive power is built upon vast amounts of experimental data accumulated over decades. Taking DeepMind’s AlphaFold as an example, its success in protein structure prediction depends heavily on the experimental results generated by scientists worldwide. While AlphaFold performs well on structures similar to those already known, its ability to infer entirely novel structures remains limited.

More broadly, scientists agree that while AI can significantly accelerate scientific progress, it is unlikely to replace scientists in the foreseeable future. “Scientists can imagine, create, and solve problems in ways that AI cannot reach—because discovery often requires stepping outside existing frameworks of knowledge and venturing into the unknown,” Kornberg explained.

As such, AI’s future role in research is more that of an assistant than a driver. “Experimental science remains the only reliable scientific method,”Frank concluded. “That will not change.”

Scientists Equipped with “Intelligent Assistants”

Yet researchers engaged in basic science often face a persistent challenge: the difficulty of clearly articulating the future applications and immediate value of their work. Fundamental discoveries—from Newton’s laws of motion and gravitation to Maxwell’s theory of electromagnetism—often took a century or more to find practical applications.

“Understanding the laws of nature has been a human dream for thousands of years,” said Wang Yifang, Director of the Institute of High Energy Physics, Chinese Academy of Sciences, in an interview with Southern Finance Omnimedia. Fundamental research, he noted, is the only path toward satisfying human curiosity and deepening our understanding of the natural world—and is therefore unquestionably worth pursuing.

Kornberg also pointed out a fundamental contradiction facing today’s scientific community: scientists generate transformative knowledge and massive amounts of data, yet often struggle to receive fair value returns within traditional systems. At the same time, the long cycle from idea to outcome appears increasingly inefficient in the AI era.

At the summit, Kornberg formally announced—on behalf of the World Laureates Association—the long-anticipated OPENSCI Initiative. “The mission of OPENSCI is to systematically reshape the value chain and collaborative model of scientific research through artificial intelligence and cryptographic technologies, allowing science to return to its essence of serving all humanity.”

According to the announcement, the initiative has two defining features:

First, it establishes a value mechanism anchored in scientific contributions, strengthening the support system for research.

Second, it develops an AI platform led by autonomous reasoning, literature retrieval, and problem-solving agents to comprehensively support scientists and researchers.

The core vehicle of this initiative, the OPENSCI Platform, is an intelligent scientific infrastructure and global collaboration network powered by AI and blockchain. Its goal is to build an efficient and transparent value feedback mechanism to better serve the global scientific community.

Built upon this foundation, OPENSCI adopts a robust three-layer architecture consisting of an application layer, Artificial Scientific Intelligence (ASCI), and underlying infrastructure. As the world’s first general scientific super-intelligent agent, ASCI marks a new stage in AI-driven research—moving from auxiliary tools toward “intelligent research assistants” capable of autonomously generating, reasoning, and validating scientific knowledge.

From strategic vision and infrastructure to core intelligent technologies, the OPENSCI Initiative aims to break through traditional efficiency bottlenecks and systematically accelerate the entire process of fundamental scientific discovery.

“In 2026, we are standing at a pivotal moment in history,” said Hou Wang, Founder, Executive Chairman, and Secretary-General of the World Laureates Association. “The future of science will not be shaped by waiting and watching, but by active participation and deliberate action.”